Greybeam

Overview

Greybeam's argument is that Snowflake cost optimisation has a ceiling, and that everyone keeps hitting it. You resize warehouses, fix auto-suspend, hunt long-running queries, drop unused tables, and then do it again next quarter. The company's own framing is that the problem is not Snowflake being inefficient, it is that every query runs on Snowflake — a dashboard query scanning 40 MB keeps a warehouse running just as a billion-row join does.

So rather than tuning the warehouse, it moves work off it. Greybeam is a query router: eligible queries go to DuckDB on its own hosted engines, everything else goes to Snowflake, and the application does not change. Its published example shows a query routed to DuckDB at 37 ms against 681 ms on Snowflake, with the routing reason given as a scan under 100 MB.

That makes it a different proposition from the other tools in this category. SELECT and Vantage tell you where the money goes; Greybeam changes where the query runs. It is a compute path by mechanism and a cost control by purpose, which is why it sits here rather than among the query engines.

Pricing is published and specific, which is rare in FinOps: $100 a month plus usage from $0.75 an hour, including hosted query engines, a managed Iceberg implementation, multi-cluster compute and a 99.99 per cent availability SLA.

Two claims to test rather than accept. Savings of 86 per cent on average, and as high as 98 per cent, are stated for read workloads specifically — not for a whole Snowflake bill. And the qualifier the company puts on it is worth repeating because it is unusually direct: if they do not think they can get there with your setup, they say so before you sign.

Key features and capabilities

The same headings are used for every cost & finops entry, so two tools can be read side by side.

What spend it covers

• Scoped to Snowflake specifically, not multi-cloud or multi-warehouse cost management
• Read workloads are where the savings are claimed, not the whole bill
• Aimed at BI, embedded analytics and agent queries

Attribution and allocation

• Each routed query carries a stated routing reason, such as a scan under 100 MB
• Latency and estimated cost are compared per query against the Snowflake baseline
• Query characteristics named in routing include aggregates, large windows, range joins and string arithmetic

Finding savings

• Routes eligible queries to DuckDB and the rest to Snowflake, rather than tuning warehouse settings
• No migration required and no application changes
• Horizontal scaling across Snowflake warehouses and multi-cluster compute
• Ad hoc Snowflake optimisation included alongside the routing itself

Budgets, forecasts and alerts

• A managed Iceberg implementation underpins the data the router reads
• Public detail on access control and audit is limited

Reporting and sharing

• A savings estimate tool is offered before purchase
• Per-query comparison of routed against baseline cost

Integrations

• Sits in the query path in front of Snowflake, so existing clients are unchanged
• Platform and GUI access included in the base fee

Where it runs and what it costs

• Hosted query engines run by Greybeam
• White glove onboarding and direct support from the founders
• 99.99 per cent availability SLA

Pricing

Subscription$100 a month plus usage from $0.75 an hour

Published and specific, which is rare in this category - $100 a month plus usage starting at $0.75 an hour, including platform and GUI access, hosted query engines, a managed Iceberg implementation, multi-cluster compute, onboarding and a 99.99 per cent availability SLA. Savings claims of 86 per cent on average apply to read workloads rather than a whole Snowflake bill.

Vendor pricing page →

Demos and videos

• Greybeam query routing Product demo · greybeam.ai (the vendor)

About Greybeam

Greybeam builds a query router that reduces Snowflake spend by executing eligible queries on DuckDB instead. It publishes its pricing openly — a monthly platform fee plus hourly usage — which is uncommon in cost optimisation, where savings-share and quote-only arrangements are the norm. Its public materials state savings of 86 per cent on average and up to 98 per cent on read workloads, and commit to telling a prospect before signing if their setup will not reach that. Support is described as coming directly from the founders, which places it at an early stage.

greybeam.ai